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A Multiobjective Strategy to Allocate Roadside Units in a Vehicular Network with Guaranteed Levels of Service

机译:保证服务水平的车辆网络中路边单元分配的多目标策略

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In this work, we propose the Delta-MGA, a specific multi-objective algorithm for solving the allocation of Roadside Units (RSUs) in a Vehicular Network (VANETs). We propose two multiobjective models to solve two different problems. The first one, our objectives are to find the minimum set of RSUs and to maximize the number of covered vehicles. The second one, our objectives are to find the minimum set of RSUs and to maximize the percentage of time that each vehicle remains connected. Our metric is based on Delta Network metric proposed in literature. As far as we concerned, Delta-MGA is the first multiobjective approach to present a deployment strategy for VANETs. We compare our approach with two mono-objective algorithms: (i) Delta-r; (ii) Delta-GA. Our results demonstrate that our approach gets better results when compared with Delta-r algorithm and competitive results when compared with Delta-GA algorithm. Furthermore, the main advantage of Delta-MGA algorithm is that with it is possible to find several different solutions given to the planning authorities diverse alternatives to deploy the RSUs.
机译:在这项工作中,我们提出了Delta-MGA,这是一种特定的多目标算法,用于解决车辆网络(VANETs)中路边单位(RSU)的分配。我们提出了两个多目标模型来解决两个不同的问题。第一个,我们的目标是找到最少的RSU集并最大化覆盖车辆的数量。第二,我们的目标是找到最少的RSU集,并最大化每辆车保持连接的时间百分比。我们的指标基于文献中提出的Delta网络指标。就我们而言,Delta-MGA是提出VANET部署策略的第一个多目标方法。我们将我们的方法与两种单目标算法进行比较:(i)Delta-r; (ii)Delta-GA。我们的结果表明,与Delta-r算法相比,我们的方法获得了更好的结果,与Delta-GA算法相比,我们的方法获得了竞争性的结果。此外,Delta-MGA算法的主要优点是可以找到给规划机构的几种不同解决方案,以部署RSU的多种选择。

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